I build AI that works when it matters most.

I'm an Associate Professor at the University of West Florida, appointed across Computer Science and Intelligent Systems & Robotics, where I direct the Artificial Super Intelligence Lab. I'm also a Research Scientist at IHMC. My research is about making agentic AI dependable: systems that perceive and act, that estimate their own uncertainty, and that are compact enough to run where the decisions actually happen.

Today my group works on three connected problems: reliability of multi-agent vision-language systems, compression that puts capable models on edge hardware, and the measurement discipline that separates real gains from lucky ones. That last thread runs through everything I do; a lot of my work is about learning not to trust the headline number.

Before UWF, I was a senior AI scientist at the U.S. Army Research Laboratory and the DoD's Joint AI Center, where I led national efforts in AI test, evaluation, and assurance, including helping secure $12M in Congressional support for AI T&E infrastructure. That operational background shapes how I think about deploying AI: reliability isn't a feature, it's the requirement.

My group trains and evaluates at cluster scale, and collaborates across defense, healthcare (including uncertainty-aware clinical decision support with Mayo Clinic), and industry. I'm always glad to talk with teams working on hard, applied AI problems.